!pip install boto3

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Installing collected packages: urllib3, jmespath, botocore, s3transfer, boto3
Successfully installed boto3-1.34.68 botocore-1.34.68 jmespath-1.0.1 s3transfer-0.10.1 urllib3-2.2.1

import boto3
import base64
import json

s3 = boto3.client('s3')
bedrock_runtime = boto3.client('bedrock-runtime', region_name='us-west-2')

# "anthropic_version": "bedrock-2023-05-31",
# "max_tokens": 4096,
# "top_k": 250,
# "top_p": 0.999,
# "temperature": 0,

def ocr_using_bedrock(file_path) :
    # 이미지 파일 읽기
    with open(file_path, 'rb') as image_file:
        image_content = image_file.read()

    # 이미지를 base64로 인코딩
    base64_encoded_image = base64.b64encode(image_content).decode('utf-8')

    # prompt = '이미지에서 텍스트를 추출해주세요. 추측하지 말고 정확하게 추출해주세요. 언어는 한글과 영어, 숫자입니다.'
    # prompt = 'Please extract text from the image. Do not guess; extract it accurately. The languages are Korean, English, and numbers'
    prompt = """
    이미지에 있는 글자를 추출해서 아래 포맷으로 작성해줘

    이미지에 있는 텍스트는 다음과 같습니다:
    {추출글자}
    """

    payload = {
        "modelId": "anthropic.claude-3-sonnet-20240229-v1:0",
        "contentType": "application/json",
        "accept": "application/json",
        "body": {
            "anthropic_version": "bedrock-2023-05-31",
            "max_tokens": 4096,
            "top_k": 250,
            "top_p": 0.999,
            "temperature": 1,
            "messages": [
                {
                    "role": "user",
                    "content": [
                        {
                            "type": "image",
                            "source": {
                                "type": "base64",
                                "media_type": "image/png",
                                "data": base64_encoded_image
                            }
                        },
                        {
                            "type": "text",
                            "text": prompt
                        }
                    ]
                }
            ]
        }
    }

    # Convert the payload to bytes
    body_bytes = json.dumps(payload['body']).encode('utf-8')

    # Invoke the model
    response = bedrock_runtime.invoke_model(
        body=body_bytes,
        contentType=payload['contentType'],
        accept=payload['accept'],
        modelId=payload['modelId']
    )

    # Process the response
    response_body = json.loads(response['body'].read())
    result = response_body['content'][0]['text']
    return result

!pip install easyocr
!pip install numpy
!pip install pretty

import io
import boto3
import easyocr
import numpy as np
import base64

from PIL import Image

from pprint import pprint

def ocr_using_easyocr(file_path) :
    file_path = file_path

    # 이미지 파일 읽기
    with open(file_path, 'rb') as image_file:
        image_content = image_file.read()

    # 이미지를 base64로 인코딩
    # base64_encoded_image = base64.b64encode(image_content).decode('utf-8')
    # image_content = image_obj['Body'].read()
    image = Image.open(io.BytesIO(image_content))
    image_np = np.array(image)






    # key = event.get('Key')
    # bucket = event.get('Bucket')
    # target_languages = event.get('TargetLanguages')
    target_languages = [
    "en",
    "ko"
  ]

#     s3_client = boto3.client('s3')

#     image_obj = s3_client.get_object(Bucket=bucket, Key=key)
#     image_content = image_obj['Body'].read()
#     image = Image.open(io.BytesIO(image_content))
#     image_np = np.array(image)


    # image_np = np.array(base64_encoded_image)

    reader = easyocr.Reader(
        target_languages,
        model_storage_directory='./',
        user_network_directory='./',
        download_enabled=True,
        gpu=False
    )
    results = reader.readtext(image_np)
    results = reader.readtext(image_np)

    detected_texts = []
    positions = []
    for result in results:
        text = result[1]
        detected_texts.append(text)

        position = result[0]
        top_left = [int(coord) for coord in position[0]]
        top_right = [int(coord) for coord in position[1]]
        bottom_right = [int(coord) for coord in position[2]]
        bottom_left = [int(coord) for coord in position[3]]
        positions.append({
            "Text": text,
            "TopLeft": {
                "x": top_left[0],
                "y": top_left[1]
            },
            "TopRight": {
                "x": top_right[0],
                "y": top_right[1]
            },
            "BottomRight": {
                "x": bottom_right[0],
                "y": bottom_right[1]
            },
            "BottomLeft": {
                "x": bottom_left[0],
                "y": bottom_left[1]
            }
        })

    detected_texts_join = ' '.join([result[1] for result in results])

    return {
        'DetectedText': detected_texts_join,
        'DetectedResults': positions
    }

import IPython.display

import os

dir_path = 'img'

for item in os.listdir(dir_path):
    file_path = os.path.join(dir_path, item)
    # file_path = 'img/sample-1.png'

    display(IPython.display.Image(filename=file_path))

    bedrock_result = ocr_using_bedrock(file_path)
    print("# BedLock - Claud3")
    print(bedrock_result)

    print("")
    print("# EasyOCR")
    easyocr_result = ocr_using_easyocr(file_path)
    pprint(easyocr_result['DetectedText'])

Using CPU. Note: This module is much faster with a GPU.

# BedLock - Claud3
이미지에 있는 텍스트는 다음과 같습니다:
동원몬행 이 행
352-1098-553

개인 정보 보호를 위해 일부 정보를 가렸습니다.

# EasyOCR
'농협은행 이 형 352-1098- 5531'

Using CPU. Note: This module is much faster with a GPU.

# BedLock - Claud3
이미지에 있는 텍스트는 다음과 같습니다:

안녕하세요 근무중이라
서옵푬매하실분만
가족ID :Vg 3

# EasyOCR
'안녕하세요 근무중이라 IO 서요구매하실분 만 카특ID :vg 8 다"다-터스 -d'

Using CPU. Note: This module is much faster with a GPU.

# BedLock - Claud3
이미지에 있는 텍스트는 다음과 같습니다:
4억원현행 176882-51-63
과, 천

# EasyOCR
'넓권온 행 176882-51- 63 과   권'

Using CPU. Note: This module is much faster with a GPU.

# BedLock - Claud3
이미지에 있는 텍스트는 다음과 같습니다:
휴먼(주) LIU ONG LIE
352-1307--53

# EasyOCR
'눈파 (주> LIU ONG LIE 352 연 1367 - -53'

Using CPU. Note: This module is much faster with a GPU.

# BedLock - Claud3
이미지에 있는 텍스트는 다음과 같습니다:
2022년 1월 18일 오후 12:44
내 계좌
농협: 352 1098 53

# EasyOCR
'< 메모 2022년 1월 18일 오후 12.44 내 계좌 농협:352 1098 53'